360 citations · 672 across the 41 of their papers we have counts for
48 papers
North Small Translate: Advanced Cost-Effective Translation (Cohere CAT+)
Tom Kocmi, Alexandre Bérard, Phil Blunsom +20
We present North Small Translate, an open-weight, LLM-based machine translation (MT) model with instruction-following capabilities built on the same foundation as Cohere's Command…
SEATauBench: Progressively Adapting Tool-Agent-User Evaluation Into Low-Resource Southeast Asian Languages
My Chiffon Nguyen, Aulia Adila, Saksorn Ruangtanusak +4
While AI development and evaluation for Southeast Asia (SEA) has grown rapidly, agent capabilities in regional languages are still poorly understood despite its importance to sover…
Anthropogenic Regional Adaptation in Multimodal Vision-Language Model
Samuel Cahyawijaya, Peerat Limkonchotiwat, Tack Hwa Wong +45
While the field of vision-language (VL) has achieved remarkable success in integrating visual and textual information across multiple languages and domains, there is still no dedic…
High-Dimensional Interlingual Representations of Large Language Models
Bryan Wilie, Samuel Cahyawijaya, Junxian He +1
Large language models (LLMs) trained on massive multilingual datasets hint at the formation of interlingual constructs--a shared subspace in the representation space. However, evid…
Linguistic Minimal Pairs Elicit Linguistic Similarity in Large Language Models
Xinyu Zhou, Delong Chen, Samuel Cahyawijaya +2
We introduce a novel analysis that leverages linguistic minimal pairs to probe the internal linguistic representations of Large Language Models (LLMs). By measuring the similarity…
LLM Internal States Reveal Hallucination Risk Faced With a Query
Ziwei Ji, Delong Chen, Etsuko Ishii +4
The hallucination problem of Large Language Models (LLMs) significantly limits their reliability and trustworthiness. Humans have a self-awareness process that allows us to recogni…
Belief Revision: The Adaptability of Large Language Models Reasoning
Bryan Wilie, Samuel Cahyawijaya, Etsuko Ishii +2
The capability to reason from text is crucial for real-world NLP applications. Real-world scenarios often involve incomplete or evolving data. In response, individuals update their…
CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark
David Romero, Chenyang Lyu, Haryo Akbarianto Wibowo +73
Visual Question Answering (VQA) is an important task in multimodal AI, and it is often used to test the ability of vision-language models to understand and reason on knowledge pres…
What Makes for Good Image Captions?
Delong Chen, Samuel Cahyawijaya, Etsuko Ishii +3
This paper establishes a formal information-theoretic framework for image captioning, conceptualizing captions as compressed linguistic representations that selectively encode sema…
High-Dimension Human Value Representation in Large Language Models
Samuel Cahyawijaya, Delong Chen, Yejin Bang +5
The widespread application of LLMs across various tasks and fields has necessitated the alignment of these models with human values and preferences. Given various approaches of hum…
Cendol: Open Instruction-tuned Generative Large Language Models for Indonesian Languages
Samuel Cahyawijaya, Holy Lovenia, Fajri Koto +13
Large language models (LLMs) show remarkable human-like capability in various domains and languages. However, a notable quality gap arises in low-resource languages, e.g., Indonesi…
LLMs Are Few-Shot In-Context Low-Resource Language Learners
Samuel Cahyawijaya, Holy Lovenia, Pascale Fung
In-context learning (ICL) empowers large language models (LLMs) to perform diverse tasks in underrepresented languages using only short in-context information, offering a crucial a…
Subobject-level Image Tokenization
Delong Chen, Samuel Cahyawijaya, Jianfeng Liu +2
Patch-based image tokenization ignores the morphology of the visual world, limiting effective and efficient learning of image understanding. Inspired by subword tokenization, we in…
LinguAlchemy: Fusing Typological and Geographical Elements for Unseen Language Generalization
Muhammad Farid Adilazuarda, Samuel Cahyawijaya, Alham Fikri Aji +2
Pretrained language models (PLMs) have become remarkably adept at task and language generalization. Nonetheless, they often fail when faced with unseen languages. In this work, we…
IndoRobusta: Towards Robustness Against Diverse Code-Mixed Indonesian Local Languages
Muhammad Farid Adilazuarda, Samuel Cahyawijaya, Genta Indra Winata +2
Significant progress has been made on Indonesian NLP. Nevertheless, exploration of the code-mixing phenomenon in Indonesian is limited, despite many languages being frequently mixe…
The Obscure Limitation of Modular Multilingual Language Models
Muhammad Farid Adilazuarda, Samuel Cahyawijaya, Ayu Purwarianti
We expose the limitation of modular multilingual language models (MLMs) in multilingual inference scenarios with unknown languages. Existing evaluations of modular MLMs exclude the…
Negative Object Presence Evaluation (NOPE) to Measure Object Hallucination in Vision-Language Models
Holy Lovenia, Wenliang Dai, Samuel Cahyawijaya +2
Object hallucination poses a significant challenge in vision-language (VL) models, often leading to the generation of nonsensical or unfaithful responses with non-existent objects.…
Survey of Social Bias in Vision-Language Models
Nayeon Lee, Yejin Bang, Holy Lovenia +3
In recent years, the rapid advancement of machine learning (ML) models, particularly transformer-based pre-trained models, has revolutionized Natural Language Processing (NLP) and…
NusaWrites: Constructing High-Quality Corpora for Underrepresented and Extremely Low-Resource Languages
Samuel Cahyawijaya, Holy Lovenia, Fajri Koto +15
Democratizing access to natural language processing (NLP) technology is crucial, especially for underrepresented and extremely low-resource languages. Previous research has focused…
GlobalBench: A Benchmark for Global Progress in Natural Language Processing
Yueqi Song, Catherine Cui, Simran Khanuja +9
Despite the major advances in NLP, significant disparities in NLP system performance across languages still exist. Arguably, these are due to uneven resource allocation and sub-opt…
Multilingual Large Language Models Are Not (Yet) Code-Switchers
Ruochen Zhang, Samuel Cahyawijaya, Jan Christian Blaise Cruz +2
Multilingual Large Language Models (LLMs) have recently shown great capabilities in a wide range of tasks, exhibiting state-of-the-art performance through zero-shot or few-shot pro…
InstructAlign: High-and-Low Resource Language Alignment via Continual Crosslingual Instruction Tuning
Samuel Cahyawijaya, Holy Lovenia, Tiezheng Yu +2
Large language models (LLMs) that are tuned with instructions have demonstrated remarkable capabilities in various tasks and languages. However, their ability to generalize to unde…
Which One Are You Referring To? Multimodal Object Identification in Situated Dialogue
Holy Lovenia, Samuel Cahyawijaya, Pascale Fung
The demand for multimodal dialogue systems has been rising in various domains, emphasizing the importance of interpreting multimodal inputs from conversational and situational cont…
A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity
Yejin Bang, Samuel Cahyawijaya, Nayeon Lee +10
This paper proposes a framework for quantitatively evaluating interactive LLMs such as ChatGPT using publicly available data sets. We carry out an extensive technical evaluation of…